Scheduling of Nonconforming Devices: The Case of a Company in the Automotive Sector

  • Mariana Araújo NogueiraEmail author
  • Maria Sameiro Carvalho
  • José António Vasconcelos
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 223)


This article presents a project developed in a company’s quality department aiming at scheduling the nonconforming devices analysis’ process. The company faced a problem of low compliance with pre-established time requests, resulting in large fines paid to its customers of the automotive sector. In order to overcome this problem, scheduling tools were developed and tested, with the goal of minimizing the number of tardy tasks in identical parallel machines. The simulation of different scheduling rules allowed confirmation that the current prioritization rule is not the most effective one. Preliminary simulations were carried out using Lekin software [18], showing that other criteria promote better results. The use of a newly developed algorithm, combining two different criteria, resulted in a reduction of tardy tasks, thus decreasing tardiness fines paid to customers. Despite the preliminary status of present results, it is possible to foresee some improvements in the analysis process performance, by using decision making support tools based on scheduling algorithms. This way, a significant improvement on the number of analysis which fulfills the defined pre-requirements will be achieved.


Quality Complaints Priorization Scheduling Lekin 



This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT– Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.


  1. 1.
    V. Armentano, D. Yamashita, Tabu search for scheduling on identical parallel machines to minimize mean tardiness. J. Intell. Manuf. 11, 453–460 (2000)CrossRefGoogle Scholar
  2. 2.
    T. ’Bagchi, Multiobjective Scheduling by Genetic Algorithms (Kluwer Aademic Pubishers, Dordrecht, 1999)Google Scholar
  3. 3.
    K. ’Baker, D. Trietsch, Principles of Sequencing and Scheduling (Wiley, London, 2009)Google Scholar
  4. 4.
    H. Barksdale, T. Powell, E. Hargrove, Complaint voicing by industrial buyers. Ind. Mark. Manag. 13, 93–99 (1984)CrossRefGoogle Scholar
  5. 5.
    J. Blackstone, D. Philliphs, G. Hogg, A state-of-the-art survey of dispatching rules for manufacturing job shop operations. Int. J. Prod. Res. 20, 27–45 (1982)CrossRefGoogle Scholar
  6. 6.
    D. Carvalho. Programação da Produção. Universidade do Minho (2000)Google Scholar
  7. 7.
    E. Coffman, Computer and Job-Scheduling Theory (Wiley, London, 1976)Google Scholar
  8. 8.
    M.A. Cohen, H.L. Lee, Out of touch with customer needs? Spare parts and after sales service. Sloan Manag. Rev. 31, 55 (1990)Google Scholar
  9. 9.
    M. Colledani, T. Tolio, Impact of quality control on production system performance. CIRP Ann. Manuf. Technol. 55, 453–456 (2006)CrossRefGoogle Scholar
  10. 10.
    T. ’Dean, S. Kambhampati, Planning and Scheduling (1997)Google Scholar
  11. 11.
    B.C. Dean. Approximation Algorithms for Stochastic Scheduling Problems. Massachusetts Institute of Techonology, 2005Google Scholar
  12. 12.
    U. Dombrowski, C. Malorny, Process identification for customer service in the field of the after sales service as a basis for lean after sales service. Procedia CIRP 47, 246–251 (2016)CrossRefGoogle Scholar
  13. 13.
    S. ’French, Sequencing and Scheduling: And Introduction to the Mathematics of the Job-Shop (Ellis Horwood, Chichester, 1982)Google Scholar
  14. 14.
    J.C. Ho, Y.-L. Chang, Minimizing the number of tardy jobs. Eur. J. Oper. Res. 84, 343–355 (1995)CrossRefzbMATHGoogle Scholar
  15. 15.
    J. ’Leung, Handbook of scheduling: Algorithms, Models and Performance Analysis (Chapman and Hall/CRC, Boca Raton, 2004)Google Scholar
  16. 16.
    C. ’Lovelock, J. Wirtz, H. Keh, X. Lu, Services Marketing in Asia, Managing People, Techonology ans Strategy (Prentice Hall International Incorporation, New Jersey, 2002)Google Scholar
  17. 17.
    S. Murali, S. Pugazhendhi, C. Muralidharan, Modelling and investigation the relationship of after sales service quality with customer satisfaction, retention and loyalty - a casa study of home appliances business. J. Retail. Consum. Serv. 30, 67–83 (2016)CrossRefGoogle Scholar
  18. 18.
    NYU Stern School of Business. LEKIN–flexible job-shop scheduling system (1998),
  19. 19.
    H. Oliver, C. Rajendran, Efficient dispatching rules for scheduling in a job shop. Int. J. Prod. Econ. 48, 87–105 (1997)CrossRefGoogle Scholar
  20. 20.
    M.A. Pes̆ić, V.J. Milić, J. Stanković, Significance of business quality management for increasing competitiveness of serbian economy. Serb. J. Manag. 7, 149–170 (2012)Google Scholar
  21. 21.
    M.L. Pinedo, Scheduling: Theory, Algorithms, and Systems (Prentice Hall, New Jersey, 2002)Google Scholar
  22. 22.
    V.T. Quy, The impact of organizational responses to complaints on posto purchase behavioral intentions via recovery satisfaction - the case of saigon commercial bank. Strateg. Manag. Q. 2, 44–79 (2014)Google Scholar
  23. 23.
    S.-O. Shim, Y.-D. Kim, Scheduling on parallel identical machines to minimize total tardiness. Eur. J. Oper. Res. 177, 135–146 (2007)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Mariana Araújo Nogueira
    • 1
    Email author
  • Maria Sameiro Carvalho
    • 2
  • José António Vasconcelos
    • 2
  1. 1.Universidade do MinhoBragaPortugal
  2. 2.Centro ALGORITMIUniversidade do MinhoGuimarãesPortugal

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